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Jan Schneider; Bibeg Limbu; Natalie Kiesler – Journal of Computing in Higher Education, 2025
Educational Technologies (EdTech) and Technology-Enhanced Learning (TEL) are established fields of academic research with the potential to transform educational practices and outcomes. Yet, they are currently facing several problems that undermine their efficacy and relevance. In this discussion paper, we examine recurrent complaints of…
Descriptors: Educational Technology, Technology Uses in Education, Technology Integration, Electronic Learning
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Ferhan Sahin; Yusuf Levent Sahin; Muhammet Recep Okur – Journal of Computing in Higher Education, 2025
While the significance of motivation in the adoption of mobile learning has been well-documented in numerous studies, empirical evidence regarding the roles of cognitive, social, and affective needs remains limited. This presents a notable gap in the field of education concerning the influence of motivational factors on mobile learning acceptance.…
Descriptors: Electronic Learning, Technology Uses in Education, Technology Integration, Adoption (Ideas)
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Xue Zhou; Christopher James MacBride Smith; Hosam Al-Samarraie – Journal of Computing in Higher Education, 2024
COVID-19 dramatically influenced students' and staff's learning and teaching experiences and approaches to learning. While many papers examined individual experiences in the context of higher education, synthesising these papers to determine enabling and hindering influences of digital adaptation was needed to guide the next phase of online…
Descriptors: COVID-19, Pandemics, Higher Education, Educational Technology
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Jelena Andelkovic Labrovic; Nikola Petrovic; Jelena Andelkovic; Marija Meršnik – Journal of Computing in Higher Education, 2025
The focus of this study was on identifying patterns of student behavior to support data-informed decision-making which would then improve the learning experience and learning outcomes of online English language courses. Learning analytics approach (or more specifically cluster analysis) was used to identify engagement patterns in online learning.…
Descriptors: Electronic Learning, Online Courses, Behavior Patterns, Student Behavior
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Thampy, Harish; Collins, Sarah; Baishnab, Elora; Grundy, Jess; Wilson, Kurt; Cappelli, Timothy – Journal of Computing in Higher Education, 2023
As a result of the COVID-19 pandemic, medical education institutions were suddenly and unexpectedly faced with making significant changes in delivering their clinical assessments to comply with social distancing requirements and limited access to clinical education centres. Seeking a potential solution to these new circumstances, we designed,…
Descriptors: Medical Education, Decision Making, Electronic Learning, Technology Uses in Education
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Marvin Evans; Elizabeth Trolli; Ashlyn Pierson; Shantanu Tilak – Journal of Computing in Higher Education, 2025
College graduates, especially teachers, often feel alienated when starting their careers as they may lack robust support systems to help them address daily difficulties. Researchers study online learning communities as a model to address this missing support system; however, very little research exists on the benefits of embedding these learning…
Descriptors: Instructional Design, Curriculum Design, Electronic Learning, STEM Education
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Cheng, Zui; Richardson, Jennifer C.; Newby, Timothy J. – Journal of Computing in Higher Education, 2020
Students' goal-setting skills are highly related to their academic learning performance and level of motivation. A review of the literature demonstrated limited research on both applicable goal-setting strategies in higher education and the support of technology in facilitating goal-setting processes. Addressing these two gaps, this study explored…
Descriptors: Recognition (Achievement), Goal Orientation, Academic Achievement, Student Motivation
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Doleck, Tenzin; Bazelais, Paul; Lemay, David John – Journal of Computing in Higher Education, 2018
It is widely recognized and accepted that behavioral intention is the key direct determinant of technology use and the majority of research continues to promote this practice. Yet the influence of behavioral intention (i.e., an individual's conscious plan to use a technology) has been called into question more recently, as behavioral intention…
Descriptors: Computer Attitudes, Intention, Technology Uses in Education, Electronic Learning
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García Botero, Gustavo; Questier, Frederik; Cincinnato, Sebastiano; He, Tao; Zhu, Chang – Journal of Computing in Higher Education, 2018
Research on mobile learning indicates that students perceive mobile devices mainly as communication and entertainment tools. Therefore, a key factor in successful mobile learning implementation is the initial measurement of students' acceptance of those devices into their learning. Countless language applications available suggest that mobile…
Descriptors: College Students, Electronic Learning, Computer Attitudes, Computer Assisted Instruction
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Mohamadi, Zohre – Journal of Computing in Higher Education, 2018
As a response to the advancement of technology into every aspect of human life especially education and the need for more involvement on the side of learners advocated by learner-centered approaches towards education, this study aimed at investigating comparative effect of project-based (PBL) learning and electronic project-based learning (EPBL)…
Descriptors: Active Learning, Student Projects, Electronic Learning, Comparative Analysis
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Bere, Aaron; Rambe, Patient – Journal of Computing in Higher Education, 2016
Research on technology adoption often profiles device usability (such as perceived usefulness) and user dispositions (such as perceived ease of use) as the prime determinants of effective technology adoption. Since any process of technology adoption cannot be conceived out of its situated contexts, this paper argues that any pre-occupation with…
Descriptors: Synchronous Communication, Computer Oriented Programs, Higher Education, Technology Uses in Education
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Hsia, Jung-Wen – Journal of Computing in Higher Education, 2016
Since mobile devices have become cheaper, easily accessible, powerful, and popular and the cost of wireless access has declined gradually, mobile learning (m-learning) has begun to spread rapidly. To further improve the effectiveness and efficiency of m-learning for university students, it is critical to understand whether they use m-learning.…
Descriptors: Handheld Devices, College Students, Higher Education, Locus of Control
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Bernard, Robert M.; Borokhovski, Eugene; Schmid, Richard F.; Tamim, Rana M.; Abrami, Philip C. – Journal of Computing in Higher Education, 2014
This paper serves several purposes. First and foremost, it is devoted to developing a better understanding of the effectiveness of blended learning (BL) in higher education. This is achieved through a meta-analysis of a sub-collection of comparative studies of BL and classroom instruction (CI) from a larger systematic review of technology…
Descriptors: Meta Analysis, Blended Learning, Technology Uses in Education, Higher Education
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Rambe, Patient – Journal of Computing in Higher Education, 2017
The rhetoric on the potential of Web 2.0 technologies to democratize online engagement of students often overlooks the discomforting, differential participation and asymmetrical engagement that accompanies student adoption of emerging technologies. This paper, therefore, constitutes a critical reality check for student adoption of technology to…
Descriptors: Foreign Countries, College Students, Cooperative Learning, Web Sites
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Guthrie, Kathy L.; McCracken, Holly – Journal of Computing in Higher Education, 2014
This article explores the use of critical reflection to facilitate the construction of knowledge resulting from participation in e-service-learning courses. Such an instructional approach integrates an interdisciplinary curricular framework with site-specific service-learning opportunities resulting in an environment richer and more accessible…
Descriptors: Reflection, Service Learning, Electronic Learning, Interdisciplinary Approach
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